When we consider our CV, it is full of entities that we are or were associated with and that define us in some way(s). Such entities include where we studied, where we worked, who we collaborated with on a project or on a paper etc. Entities we are linked to are part of who we are and may reveal about what we are interested in. Hence, we can view any CV as a graph of interlinked entities, where nodes are entities and edges are relations between them. This study proposes a novel entity search framework that in response to a real-time query about an entity, searches, crawls, analyzes and consolidates relevant information that is freely available on the Web about the entity of interest, culminating in the generation a profile of the searched entity. Unlike typical entity search settings, in which a ranked list of entities related to the target entity over a pre-specified relation is processed, we present and visualize rich information about the entity of interest as a typed entity-relation graph without an apriori definition of the types of related entities and relations. This view is structured and compact, making it easy to understand as well as interpret. It enables the user to learn not only about the entity in question, but also about related entities, thereby obtaining a better understanding of the entity in question. We evaluated each of the frameworks components separately and then performed an overall evaluation of the framework, its visualization and the interest of users in the results. The results show that the proposed framework performs entity searches, related entity identification and relation identification very well and that it satisfies users needs.
翻译:当我们考虑我们的CV时,它充满了我们有或曾经有关系的实体,并且以某种方式定义了我们。这些实体包括我们研究过、我们工作过、我们在一个项目上或纸上合作过、我们与谁合作过等等。我们联系的实体是我们是谁的一部分,并且可能透露我们感兴趣的。因此,我们可以将任何CV视为一个相互联系实体的图表,其中节点是实体和边缘是它们之间的关系。本研究报告提出一个新的实体搜索框架,回应关于一个实体、搜索、爬行、分析和合并的实时查询。这些实体包括我们在网上自由获得的关于利益实体的相关信息,最终形成一个被搜索实体的概况等等。与典型的实体搜索设置不同,其中处理一个与目标实体有关的实体在预定关系中的实体的排名清单,我们将有关该实体的丰富信息作为类型实体关系图表加以展示和视觉化的图,而不必对相关实体的类型和关系作出最优先的定义。这种观点是结构化和紧凑凑的,使得它很容易理解有关实体的搜索关系,最终形成一个被搜索的实体的概况。这样,我们就可以对每个实体进行深入评估,然后才能了解一个相关的框架。我们所评估的用户,我们所了解的一个问题。